A New Approach to Simplifying and Harmonizing Cancer Clinical Trials-Standardizing Eligibility Criteria

North American Cancer Center Clinical Research Capacity and Benchmarking in the Postpandemic Era

PURPOSE

Cancer center clinical trial offices (CCTOs) support trial development, activation, conduct, regulatory adherence, data integrity, and compliance. In 2018, the Association of American Cancer Institutes (AACI) Clinical Research Innovation (CRI) Steering Committee conducted and published survey results to benchmark North American CCTOs, including trial volume, accrual, full time equivalents (FTEs), and budget. The survey was readministered in 2023 to assess contemporary CCTO performance and capacity with results presented here.

METHODS

The 28 question 2023 survey was sent to directors of AACI's clinical member cancer centers. Survey participation was voluntary, no compensation was provided, and data requested covered operations during 2022. Definitions were consistent with National Cancer Institute (NCI) CCTO reporting requirements and AACI staff anonymously compiled results for descriptive statistical reporting.

RESULTS

The survey response rate was 61% (60/99). The median annual CCTO budget was $11.5 million (M) US dollars (USD) versus $8.2M USD in 2018. These budgets support a median of 150 FTEs versus 104 previously, and a median total of 384 versus 280 interventional treatment trials and a median of 479 versus 531 interventional treatment accruals. Sources of support for CCTO annual budgets were primarily from industry revenue (45.3%) or institutional support (31.7%). Nearly 60% of centers reported activating NCI-sponsored studies within 90 days but only 9% reported meeting a 90-day activation timeline for industry sponsored studies.

CONCLUSION

Contemporary benchmarks for CCTO operations through this survey demonstrate larger staff sizes, larger budgets, more trials supported, but fewer patients enrolled to interventional treatment trials in comparison with 2018. These data shine a critical light on the increasing complexity of cancer clinical trials, the importance of external funding sources, and necessary operational efficiency upgrades to provide cutting-edge cancer research and care.

Brief Report: Real-World Eligibility for Clinical Trials in Patients With Extensive-Stage SCLC at a Tertiary Care Center

Introduction

The CASPIAN and IMpower133 trials revealed a significant survival benefit of chemotherapy plus immunotherapy in patients with extensive-stage SCLC. The current study characterizes the proportion of real-world patients who would have met eligibility for these trials and highlights factors influencing eligibility in the real-world setting.

Methods

A retrospective analysis of patient data was conducted for stage IV patients with SCLC treated at the Cancer Centre of Southeastern Ontario, Canada. Trial eligibility was based on criteria used in the IMpower133 and CASPIAN trials. Data were summarized using descriptive statistics. Overall survival was assessed using the Kaplan-Meier method.

Results

Of the 116 patients included, only 12.1% met the overall eligibility criteria for the IMpower133 trial, and 14.7% for the CASPIAN trial. The most common reasons for ineligibility included: Eastern Cooperative Oncology Group (ECOG) 2 or greater (77.5%), inadequate organ function (48%), and the presence of brain metastases at diagnosis (37.3%). Sixty-one patients (59.8%) met two or more major ineligibility criteria. If trial eligibility was expanded to include ECOG 2 patients, an additional 10.3% would have met eligibility. The median overall survival for all-comers was 6.5 months.

Conclusions

Only a small minority of real-world patients with extensive-stage SCLC would have met eligibility for the IMpower133 and CASPIAN trials, with ECOG greater than or equal to 2, inadequate organ function, and brain metastases comprising the most common reasons for trial ineligibility. Future clinical trials should expand the inclusion criteria to better represent real-world patient populations.

What Is Ailing Oncology Clinical Trials? Can We Fix Them?

Evidence from phase three clinical trials helps shape clinical practice. However, a very small minority of patients with cancer participate in clinical trials and many trials are not completed on time due to slow accrual. Issues with restrictive eligibility criteria can severely limit the patients who can access trials, without any convincing evidence that these restrictions impact patient safety. Similarly, regulatory, organizational, and institutional hurdles can delay trial activation, ultimately making some studies irrelevant. Additional issues during trial conduct (e.g., mandatory in-person visits, central confirmation of standard biomarkers, and inflexible drug dosage modification) contribute to making trials non-patient-centric. These real-life observations from experienced clinical trialists can seem nonsensical to investigators and patients alike, who are trying to bring effective drugs to patients with cancer. In this review, we delve into these issues in detail, and discuss potential solutions to make clinical trials more accessible to patients.

Quantitative evaluation of the impact of relaxing eligibility criteria on the risk-benefit profile of drugs for lung cancer based on real-world data

INTRODUCTION

Restrictive eligibility criteria in cancer drug trials result in low enrollment rates and limited population diversity. Relaxed eligibility criteria (REC) based on solid evidence is becoming necessary for stakeholders worldwide. However, the absence of high-quality, favorable evidence remains a major challenge. This study presents a protocol to quantitatively evaluate the impact of relaxing eligibility criteria in common non-small cell lung cancer (NSCLC) protocols in China, on the risk-benefit profile. This involves a detailed explanation of the rationale, framework, and design of REC.

METHODS

To evaluate our REC in NSCLC drug trials, we will first construct a structured, cross-dimensional real-world NSCLC database using deep learning methods. We will then establish randomized virtual cohorts and perform benefit-risk assessment using Monte Carlo simulation and propensity matching. Shapley value will be utilized to quantitatively measure the effect of the change of each eligibility criterion on patient volume, clinical efficacy and safety.

DISCUSSION

This study is one of the few that focuses on the problem of overly stringent eligibility criteria cancer drug clinical trials, providing quantitative evaluation of the effect of relaxing each NSCLC eligibility criterion. This study will not only provide scientific evidence for the rational design of population inclusion in lung cancer clinical trials, but also establish a data governance system, as well as a REC evaluation framework that can be generalized to other cancer studies.

Eligibility criteria: too big, too small or just right?

Not available.

Placebo-controlled randomized clinical trials of antidepressants for major depressive disorder: Analysis of ClinicalTrials.gov, 2008-2022

The purpose of this study was to analyze the key aspects of the design of contemporary placebo-controlled randomized clinical trials (RCTs) of antidepressants enrolling patients with major depressive disorder (MDD) aged 18 years or older, especially the outcome measures and the eligibility criteria. The study included 122 RCTs registered with ClinicalTrials.gov and started from 2008 through 2022. Most RCTs assessed only clinical remission, with proportion of trials with outcome measures related to functional remission being rather low (n = 34; 28 %). Clinical remission was mostly evaluated in acute phase of depression, and only 7 (6 %) trials assessed the prevention of relapse. Proportion of trials utilizing self-report questionnaires that provide important information complementary to clinician-rated scales was moderate (n = 66; 54 %). Another problem in included RCTs was common use of stringent eligibility criteria. For instance, minimal symtpom severity required for the patient's inclusion was listed in 104 RCTs (85 %), and 41 RCTs (34 %) excluded patients based on comorbid anxiety disorders. Most RCTs (n = 103; 84 %) excluded older patients, and only 6 (5 %) trials were dedicated exclusively to them. To ensure optimal development of clinical pharmacotherapy of MDD, the investigators should consider modification of some of the key aspects of the design of RCTs of antidepressants.

Examining Exclusion Criteria in Advanced Prostate Cancer Clinical Trials: An Assessment of recommendations From the American Society Of Clinical Oncology and Friends of Cancer Research

PURPOSE

Eligibility criteria illustrate the characteristics of the study population and promote the safety of participants. However, overreliance on restrictive eligibility criteria may limit the generalizability of outcomes. As a result, the American Society of Clinical Oncology (ASCO) and Friends of Cancer Research (Friends) issued statements to curtail these challenges. In this study, we aimed to assess restrictiveness in eligibility criteria across advanced prostate cancer clinical trials.

MATERIALS AND METHODS

We identified all phase I, II, and III advanced prostate cancer clinical trials between June 30, 2012, and June 30, 2022, through Clinicaltrials.gov. We evaluated whether a clinical trial excluded, conditionally included, or did not report 4 common criteria: brain metastases, prior or concurrent malignancies, HIV infection, and hepatitis B virus (HBV)/hepatitis C virus (HCV) infection. Performance status (PS) criteria were recorded based on the Eastern Cooperative Oncology Group (ECOG) scale.

RESULTS

Out of 699 clinical trials within our search strategy, 265 (37.9%) trials possessed all the required data and were included in our analysis. The most common excluded condition of our interest was brain metastases (60.8%), followed by HIV positivity (46.4%), HBV/HCV positivity (46.0%), and concurrent malignancies (15.5%). Additionally, 50.9% of clinical trials only included patients with ECOG PS 0 to 1. HIV and HBV/HCV infection were exclusion criteria of 22 (80.8%) and 19 (73.1%) immunotherapy trials, respectively.

CONCLUSION

Patients with brain metastases, prior or concurrent malignancies, HIV infection, HBV/HCV infection, or low-functioning PS were overly restricted from participating in advanced prostate clinical trials. Advocating for broader criteria may ameliorate generalizability.

Travel Time and Distance and Participation in Precision Oncology Trials at the National Cancer Center Hospital

Importance

Genotype-matched trials, which are becoming increasingly important in the precision oncology era, require referrals from institutions providing comprehensive genomic profiling (CGP) testing to those conducting these trials, and the travel burden for trial participation is significant. However, it remains unknown whether travel time or distance are associated with genotype-matched trial participation.

Objective

To assess whether travel time or distance are associated with disparities in genotype-matched trial participation following CGP testing.

Design, Setting, and Participants

This retrospective cohort study from June 2020 to June 2022 included patients with advanced or metastatic solid tumors referred to the National Cancer Center Hospital for participation in genotype-matched trials following CGP testing and discussion by molecular tumor boards. Data were analyzed from June to October 2022.

Exposures

Travel time and distance.

Main Outcomes and Measures

The primary and secondary outcomes were enrollment in genotype-matched trials and all-cancer clinical trials, respectively.

Results

Of 1127 patients (mean [range] age, 62 [16-85] years; 584 women [52%]; all residents of Japan), 127 (11%) and 241 (21%) were enrolled in genotype-matched trials and all-cancer clinical trials, respectively. The overall median (IQR) travel distance and time were 38 (21-107) km and 55 (35-110) minutes, respectively. On multivariable regression with 23 covariates, travel distance (≥100 km vs <100 km) was not associated with the likelihood of genotype-matched trial participation (26 of 310 patients [8%] vs 101 of 807 patients [12%]; odds ratio [OR], 0.64; 95% CI, 0.40-1.02), whereas in patients with travel time of 120 minutes or more, the likelihood of genotype-matched trial participation was significantly lower than those with travel time less than 120 minutes (19 of 276 patients [7%] vs 108 of 851 patients [13%]; OR, 0.51; 95% CI, 0.29-0.84). The likelihood of genotype-matched trial participation decreased as travel time increased from less than 40 (38 of 283 patients [13%]) to 40 to 120 (70 of 568 patients [12%]) and 120 or more (19 of 276 patients [7%]) minutes (OR, 0.74; 95% CI, 0.48-1.17; OR, 0.41; 95% CI, 0.22-0.74, respectively). Neither travel time nor distance were associated with the likelihood of all-cancer clinical trial participation.

Conclusions and Relevance

In this cohort study of patients undergoing CGP testing, an increased travel time was associated with a decreased likelihood of genotype-matched trial participation. This warrants further research on interventions, such as decentralization of clinical trials to mitigate travel burden.

How to Improve Cancer Patients ENrollment in Clinical Trials From rEal-Life Databases Using the Observational Medical Outcomes Partnership Oncology Extension: Results of the PENELOPE Initiative in Urologic Cancers

PURPOSE

To compare the computability of Observational Medical Outcomes Partnership (OMOP)-based queries related to prescreening of patients using two versions of the OMOP common data model (CDM; v5.3 and v5.4) and to assess the performance of the Greater Paris University Hospital (APHP) prescreening tool.

MATERIALS AND METHODS

We identified the prescreening information items being relevant for prescreening of patients with cancer. We randomly selected 15 academic and industry-sponsored urology phase I-IV clinical trials (CTs) launched at APHP between 2016 and 2021. The computability of the related prescreening criteria (PC) was defined by their translation rate in OMOP-compliant queries and by their execution rate on the APHP clinical data warehouse (CDW) containing data of 205,977 patients with cancer. The overall performance of the prescreening tool was assessed by the rate of true- and false-positive cases of three randomly selected CTs.

RESULTS

We defined a list of 15 minimal information items being relevant for patients' prescreening. We identified 83 PC of the 534 eligibility criteria from the 15 CTs. We translated 33 and 62 PC in queries on the basis of OMOP CDM v5.3 and v5.4, respectively (translation rates of 40% and 75%, respectively). Of the 33 PC translated in the v5.3 of the OMOP CDM, 19 could be executed on the APHP CDW (execution rate of 58%). Of 83 PC, the computability rate on the APHP CDW reached 23%. On the basis of three CTs, we identified 17, 32, and 63 patients as being potentially eligible for inclusion in those CTs, resulting in positive predictive values of 53%, 41%, and 21%, respectively.

CONCLUSION

We showed that PC could be formalized according to the OMOP CDM and that the oncology extension increased their translation rate through better representation of cancer natural history.